As Investors Ask AI For Broker Picks, A New Visibility Race Emerges

CRE brokers are no longer just competing for referrals from clients. In the age of artificial intelligence, they’re competing for referrals from algorithms. 

As generative AI tools increasingly tell investors whom to call, brokers who carve out a clear niche and feed the machines a steady diet of deal data and thought leadership are emerging as the industry’s new AI‑visible power players.

“I would say the biggest challenge for a lot of brokers who are not 30 years in the business is just brand awareness, awareness of what you do, what differentiates you,” said Taylor Avakian, a first vice president at Lyon Stahl Investment Real Estate. “It's a foot-in-the-front-door situation.” 

For brokers without decades of name recognition, AI represents a rare opening: a way to get in front of investors they’d otherwise never meet. Early adopters say chatbot referrals are already translating into real‑world meetings, even if they still make up a small share of overall business. 

And while the technology remains uneven, with some markets still lacking enough structured data for AI to make recommendations, the brokers who are leaning in are now positioning themselves to capture a wave of algorithm‑driven discovery that’s only beginning to take shape.

A new ranking of nearly 2,700 Los Angeles CRE brokers’ visibility in AI recommendations puts a national capital markets chief who closed $2.6B in 2024 deals in the top spot, followed by Avakian, who logged $65M in 2025. The diversity of the list is symbolic of the opportunity that AI recommendations present. 

“It's like any big evolution in technology — there are certain people who can adapt quickly and benefit a lot from it,” said Nils Urbaniak, co-founder of AI visibility platform ViewEO, which compiled the list.

For decades, business owners from entrepreneurs to billionaires were focused on improving their organic internet search results, frequently through search engine optimization, or SEO. Optimizing your website and online presence for SEO usually meant using keywords that caught the eye of Google and pushed your results to the top of an endless list. 

But now, the top of a Google search is occupied by AI results. With the use of generative AI platforms like Claude and ChatGPT for a growing swath of daily tasks, many in commercial real estate are starting to look at marketing efforts with generative AI in mind. 

AI presents a front on which a smaller or newer entrant might get their name out to a wider audience, including prospective clients they might never have met. 

Avakian has already made connections with sophisticated investors with $6M to $12M to spend because ChatGPT recommended they contact him. 

Like SEO, there are some emerging patterns of what AI looks for, ViewEO co-founder Liam Mulcahy said. It likes specificity because it wants to recommend experts, so brokers who work in defined areas and publicize their deals in that space have a leg up. 

Brokerages with thought leadership pieces authored by real brokers, market reports and market insights are also positioned to establish themselves as authorities. If news outlets or other social media users write about or share those assets, that also helps boost visibility of brokers. 

“AI is not making real decisions, it's just aggregating narratives,” Mulcahy said. 

Brokers who are doing a high volume of pricey deals in their markets are still likely to have solid AI visibility, as is the case with Newmark’s Kevin Shannon, who was in the top spot on the LA list. Brokers doing large deals but without a strong AI profile aren’t going to see significant negative impacts, but it might be something that affects them at the margins, Urbaniak said. 

“They're not going to go from doing $50M a year to doing $1M, but they might do $49M,” Mulcahy said.  

In one case in Brooklyn, New York, ViewEO found that a small boutique brokerage, Terra CRG, was outperforming the top five largest in AI recommendations. By specializing in Brooklyn, doing deals exclusively there, publicizing those deals and having research and neighborhood guides specifically targeted to Brooklyn, the firm was able to dramatically boost its profile for generative AI. 

Sometimes, AI is still searching for brokers whose expertise is framed in a way it can recognize to promote. In parts of Virginia, AI wasn’t able to recommend a CRE broker 25% of the time it was prompted for the best CRE brokers, Urbaniak said. 

“There is still a lot of white space for people to grab and build that authority in those markets,” Urbaniak said. 

At Matthews Real Estate Investment Services, the brokerage affiliated with the No. 3 broker on the list, a solid AI recommendation strategy entails more or less the same plan of attack that has guided the team since before ChatGPT was a glimmer in anyone’s eye: promote agents, their deals, their thoughts on trends and market analysis, Matthews Vice President of Marketing Lori Girgis said.

“[Large language models] are looking for genuine, insightful, valuable content,” Matthews Chief Technology Officer Sean Clancy said. “They're prioritizing that, and we've never lost focus on that.”

The brokerage is seeing an increase month-over-month in contacts from various generative AI chatbot referrals, Girgis said.

Because these efforts are part of the overall marketing plan, Girgis was unable to break out exactly how much money is being spent on AI optimization.

Lyon Stahl, which has two brokers on the list, Avakian and multifamily broker Jake Glaser, said it’s shifting more resources toward AI as it continues to test what works, but was not yet able to disclose what amount of its marketing budget was devoted to these efforts. 

“It's an investment we're taking seriously,” a representative wrote in an email.

It’s unclear what percentage of clients are finding brokers through AI recommendations versus other sources, including traditional referrals, cold calls by brokers and Google searches. 

Anecdotally, the recommendations are trickling in and are meaningful for the brokers who are already benefiting from them. 

Within the last couple of months, Avakian knows five people have cold-called him because ChatGPT recommended him. Those leads have all translated to lunches and meetings — a better conversion rate than traditional cold-calling, he said. 

The rise in AI recommendations wasn’t totally surprising to him, as he’s been working with a branding and marketing team. 

“You kind of try these things, you don't know if they're going to work, and it's really cool to see that they actually are having an effect on my business,” Avakian said. 

Overall, Avakian estimates that 90% of his business is still from more traditional forms of referrals and only about 10% is from ChatGPT, with the caveat that it’s still very early for AI recommendations and he’s had years to build up a network for personal referrals. 

Matthews Senior Vice President and National Director Michael Pakravan, a retail leasing specialist with more than two decades of experience, was third on the list for AI visibility in Los Angeles. 

Despite his position on the list, Pakravan said he’s yet to have a prospective client who has found him through AI, though he admits he doesn’t ask 100% of all out-of-the-blue clients how they found him. He estimates that personal referrals and his signage around town and on buildings he works on are his two largest lead sources by far.

As part of his position as the national retail leasing director, Pakravan has to help generate lists of expert brokers in new cities and towns across the country to talk to and potentially recruit when new offices are opened. He usually starts by using AI to assemble a solid list. 

It’s just the first step, and he always cross-checks it against other sources, but “it's great for putting lists like that together,” he said.